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Automate Amazon Bedrock batch inference: Building a scalable and efficient pipeline

AWS Machine Learning - AI

To address this consideration and enhance your use of batch inference, we’ve developed a scalable solution using AWS Lambda and Amazon DynamoDB. We walk you through our solution, detailing the core logic of the Lambda functions. Amazon S3 invokes the {stack_name}-create-batch-queue-{AWS-Region} Lambda function.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

However, this method presents trade-offs. Semantic routing offers several advantages, such as efficiency gained through fast similarity search in vector databases, and scalability to accommodate a large number of task categories and downstream LLMs. However, it also presents some trade-offs.

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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning - AI

Before processing the request, a Lambda authorizer function associated with the API Gateway authenticates the incoming message. After it’s authenticated, the request is forwarded to another Lambda function that contains our core application logic. This request contains the user’s message and relevant metadata.

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Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning - AI

The solution presented in this post takes approximately 15–30 minutes to deploy and consists of the following key components: Amazon OpenSearch Service Serverless maintains three indexes : the inventory index, the compatible parts index, and the owner manuals index.

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Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning - AI

This post presents a solution where you can upload a recording of your meeting (a feature available in most modern digital communication services such as Amazon Chime ) to a centralized video insights and summarization engine. You can invoke Lambda functions from over 200 AWS services and software-as-a-service (SaaS) applications.

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How BQA streamlines education quality reporting using Amazon Bedrock

AWS Machine Learning - AI

Amazon SQS serves as a buffer, enabling the different components to send and receive messages in a reliable manner without being directly coupled, enhancing scalability and fault tolerance of the system. The text summarization Lambda function is invoked by this new queue containing the extracted text.

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Building a virtual meteorologist using Amazon Bedrock Agents

AWS Machine Learning - AI

Although weather information is accessible through multiple channels, businesses that heavily rely on meteorological data require robust and scalable solutions to effectively manage and use these critical insights and reduce manual processes. There is also memory retention across the interaction allowing a more personalized user experience.